Search

Funding Information: This research was supported by the California Energy Commission (CEC) Electric Program Investment Charge grant EPC-16-013, with cost share provided by Big Ass Fans, and cost share and additional support from Center for the Built Environment. We are thankful to many additional people who were involved in and contributed to this research project. At the CBE: Edward Arens, Fred Bauman, Wenhua Chen, Carlos Duarte, Yingdong He, Maohui Luo, Yang Li, Amy Mostacho, Jovan Pantelic, Tom Parkinson, Elaina Present, Stefano Schiavon, and Wang Zi. At TRC: Kristen Bellows and Abhijeet Pande. At the UC Berkeley Buildings, Energy, and Transportation Systems lab in the School of Electrical Engineering and Computer Science: Gabe Fierro and Michael Andersen for the Hamilton dataloggers and associated server. At Big Ass Fans: Jay Fizer, Michael Harp, Pete Maley, Justin Risner, Michael Smith, Christian Taber, Jayme Webb, Oleg Dantchenko, Funding Information: This research was supported by the California Energy Commission (CEC) Electric Program Investment Charge grant EPC-16-013, with cost share provided by Big Ass Fans, and cost share and additional support from Center for the Built Environment. We are thankful to many additional people who were involved in and contributed to this research project. At the CBE: Edward Arens, Fred Bauman, Wenhua Chen, Carlos Duarte, Yingdong He, Maohui Luo, Yang Li, Amy Mostacho, Jovan Pantelic, Tom Parkinson, Elaina Present, Stefano Schiavon, and Wang Zi. At TRC: Kristen Bellows and Abhijeet Pande. At the UC Berkeley Buildings, Energy, and Transportation Systems lab in the School of Electrical Engineering and Computer Science: Gabe Fierro and Michael Andersen for the Hamilton dataloggers and associated server. At Big Ass Fans: Jay Fizer, Michael Harp, Pete Maley, Justin Risner, Michael Smith, Christian Taber, Jayme Webb, Oleg Dantchenko, David Walton, and installers and electricians. This research would not have been possible without the support of staff and facility managersat all of the field sites, and we are grateful for their collaboration. This work used computational resources from the Extreme Science and Engineering Discovery Environment (XSEDE) which is supported by National Science Foundation grant number ACI-1548562, specifically the Jetstream cloud compute resources at Indiana University through allocation ECS180009. Funding Information: David Walton, and installers and electricians. This research would not have been possible without the support of staff and facility managers at all of the field sites, and we are grateful for their collaboration. This work used computational resources from the Extreme Science and Engineering Discovery Environment (XSEDE) which is supported by National Science Foundation grant number ACI-1548562, specifically the Jetstream cloud compute resources at Indiana University through allocation ECS180009. Publisher Copyright: © 2021 The Author(s) Controlled air movement is an effective strategy for maintaining occupant comfort while reducing energy consumption, since comfort at moderately warmer temperatures requires less space cooling. Modern ceiling fans provide a 2–4 °C cooling effect at power consumption comparable to LED lightbulbs (2–30 W) with gentle air speeds (0.5–1 m/s). However, very limited design guidance and performance data are available for using ceiling fans and air conditioning together, especially in commercial buildings. We present results from a 29-month field study of 99 automated ceiling fans and 12 thermostats installed in ten air-conditioned buildings in a hot/dry climate in California. Staging ceiling fans to automatically cool before, and then operate together with air conditioning enabled raising air conditioning cooling temperature setpoints in most zones, with overall positive occupant interview and survey responses. Overall measured cooling season (April– October) compressor energy savings were 36%, normalized by floor area served (41% during summer peak billing hours). Weather-normalized changes in zone energy use varied from 24% increase to 73% decrease across 13 compressors, reflecting variation in occupant schedules and other uncontrolled factors in occupied buildings. Median weather-normalized energy savings per compressor were 21%. Staging ceiling fans and air conditioning provided comfort across a wider temperature range, using less energy, than air conditioning alone.

Current thermal comfort standards use Predicted Mean Vote (PMV) classes as the compliance criteria despite previous critiques. The implicit assumption is that a narrower PMV range ensures higher thermal acceptability among building occupants. However, our analysis of a global database of thermal comfort field studies demonstrates that PMV classes are not appropriate design compliance criteria, and reinforces the need for a new and robust approach to thermal comfort compliance assessment. We compared two statistical methods to derive acceptable temperature ranges from occupant responses applied one to the ASHRAE Global Thermal Comfort Database II. Derived acceptable temperature ranges in real buildings (7.4K-12.2 K) using this new method are wider than the current standards mandate (2 K-6K). Our findings support the call for a relaxation of suggested temperature ranges in thermal comfort standards so as to minimize unnecessary space conditioning. The proposed data-driven statistical methods to determine temperature design compliance criteria are viewed as an important step forward in the age of continuous and pervasive monitoring and the associated large databases of building comfort measurements.

The ever-increasing demand for built spaces to cater to the needs of the tropical population compels for the adoption of sustainable building forms and passive design strategies. This research aims at studying the cases of six naturally ventilated occupied buildings constructed in the tropical ‘warm and humid’ climate of Pondicherry and Auroville, India. The buildings were subjected to long-term data logging and sporadic hand-held measurements. Indoor parameters of air temperature (Ta), surface temperature (Ts), and relative humidity (RH) across six living spaces, eight roof assemblies, and six passive design strategies were logged on an hourly basis and analysed for the hottest and coldest months. In order to estimate the thermal comfort, Ta readings of the most occupied zones were compared against ASHRAE-55 adaptive thermal comfort model and India Model for Adaptive Comfort (IMAC) temperature limits. This research showed that the hourly averaged Ta and RH in the six naturally ventilated spaces at the hottest summer hour (13:00) was between 31.0 and 33.2 °C and 56.0–69.0% while the outdoors were at 36.9 °C and 43.3% respectively. The hourly averaged rooftop and ceiling Ts for the unshaded roofs at 14:00 h during peak summer was between 53.0-43.4 °C and 36.6–31.0 °C respectively, while a shaded roof had a rooftop and ceiling Ts of 34.5 °C and 31.9 °C respectively. The passive design strategies of exposed cavity walls, night ventilation, and optimised building forms were found to be the most effective. The number of uncomfortable hours predicted by the ASHRAE model were found to be 93.4% higher than those by IMAC.

Natural ventilation has emerged as a desirable feature of sustainable buildings given its potential positive impact on building energy performance and amenities for occupants. In some circumstances, natural ventilation can provide a higher ventilation rate compared to mechanical ventilation, thus improving the air quality of indoor space, resulting in lower indoor carbon dioxide and volatile organic compound concentrations. However, this increased ventilation rate also raises the issue of increased indoor pollutant concentration from outdoor sources, which has been proven to significantly affect occupant health. In this paper, we investigate the influence of three major outdoor air pollutants, PM2.5, PM10, and ozone, on natural ventilation usage across 12 major US cities and their corresponding climate zones utilizing the outdoor air pollutant records from the US Environmental Protection Agency. Firstly, a descriptive statistics study presents a general description of air pollutant records in these investigated cities and climate zones. Then two natural ventilation operation scenarios (considering outdoor air pollutants vs. not) are developed and compared to explicitly show the expected natural ventilation reduction in these areas. The investigation results indicate that the most polluted area for natural ventilation is Los Angeles (with a projected 70% reduction), followed by Chicago (approximately 40% reduction), and then Atlanta and San Francisco (20–30% reduction for each). The natural ventilation reduction caused by outdoor air pollutants ranges from 5% to 20% in all other tested cities. Among the three pollutants (PM2.5, PM10, and ozone) we investigated, the influence of PM2.5 consistently emerges as the most critical to consider, while the impact of PM10 is typically trivial. The influence of ozone is not obvious in most cases. Nevertheless, in certain cases, its influence is non-negligible when natural ventilation is utilized. This study aims to provide a general guideline for decision makers to consider the influence of outdoor air quality on natural ventilation usage when adopting natural ventilation in different US locations. The results also confirmed the outdoor air pollutants, especially PM2.5, as a significant factor to consider in the natural ventilation design to shield the occupant from excessive air pollutant exposure.

India has a rich tradition of climate responsive architecture, incorporating several variations of passive design strategies that have been layered over time with the cultural, social and environmental context of the immediate geographical region. Designing climate responsive buildings is challenging, requiring an understanding of building physics, as well as the way buildings are designed, constructed and operated in a given cultural context. The process becomes more difficult with the ever-increasing comfort expectations. Unfortunately, it is easier to install air conditioners in a poorly designed building than to design a high-performing building to begin with. This paper is based on a study to evaluate the thermal performance of climate responsive buildings. We studied six modern institutional and office buildings in warm-humid, hot-dry and composite climate zones. Collectively, they incorporated a range of passive and hybrid design strategies, including various shading devices, courtyards, solar chimneys, cavity walls, various configurations of thermal mass, day and night-time ventilation, and evaporative cooling. We monitored each building for a period of one year and assessed their performance in terms of the behaviour of selected components, their overall response to the prevailing outdoor conditions. In addition to the measured variables, we compared performance using temperature gradients overlay on wall sections, heat maps and linear regression analysis to understand the relationship between the outdoor and indoor conditions to determine the nature of “climate responsiveness” of each building.

Advances in heating, ventilation and air conditioning (HVAC) technologies have dramatically improved the indoor thermal environment, but attention should be paid on how this would affect building occupants' thermal comfort perception. In this paper, we studied the mutually dependent relationship between indoor climate experience and occupants' comfort expectation. An intriguing experiment was conducted in China where wintertime indoor thermal environments in northern cities (with district heating) are much warmer than in southern region (without district heating). By analyzing the 4411 responses from four college-aged subject groups with different indoor thermal history, two interesting findings emerged. Firstly, people's understandings of thermal comfort change with their indoor thermal experiences. Those permanently live in lower-grade non-neutral thermal environment can achieve similar thermal comfort perception as those who live in long-term comfortable thermal conditions. Secondly, the dynamics of building occupants' thermal comfort adaptation project asymmetric trajectories. It is much quicker for occupants to accept neutral indoor climate than to lower their expectation and adapt to under-conditioned environments. These two phenomena can be well described by the index “demand factor”, which can serve as a reference for future thermal comfort study.

This work presents a novel approach for exploratory analysis of indoor environment measurements. Building monitoring is a complex task constrained by technological and environmental limits. Monitoring processes can be long, employ multiple sensors and equipment, and may involve multiple buildings across extended periods. Once the data is collected, it's not always straightforward how to make sense of it. When faced with complex heterogeneous amounts of data, early exploratory analysis is helpful to make sense of the broad patterns, highlight data weaknesses and features, and identify directions for more in-depth analysis. Inaccuracy, incompleteness and inconsistence are common characteristics of monitored field data, which then often needs intensive pre-processing to address data quality issues and improve data analysis results. This paper describes techniques from computer science, such as decision tree induction and others, that are not normally applied to field measurements of indoor environments in buildings, and as an example applies them to a complex set of data from climate-responsive spaces in India. The findings illustrate the power of these techniques for using simplified measures as proxies to extract more sophisticated information about building operation, and for quickly identifying patterns in how different design and operational characteristics affect thermal comfort.

Green-building certification systems aim at improving the design and operation of buildings. However, few detailed studies have investigated whether a green rating leads to higher occupant satisfaction with indoor environmental quality (IEQ). This research builds on previous work to address this. Based on the analysis of a subset of the Center for the Built Environment Occupant Indoor Environmental Quality survey database featuring 11,243 responses from 93 Leadership in Energy and Environmental Design (LEED)-rated office buildings, this study explores the relationships between the points earned in the IEQ category and the satisfaction expressed by occupants with the qualities of their indoor environment. It was found that the achievement of a specific IEQ credit did not substantively increase satisfaction with the corresponding IEQ factor, while the rating level, and the product and version under which certification had been awarded, did not affect workplace satisfaction. There could be several reasons for this, some of which are outside the control of designers and beyond the scope of rating systems based primarily on design intent. The challenges and priorities facing building professionals, researchers and green building certification systems are discussed for the creation of more comfortable, higher performing and healthier green-rated buildings.

Plug loads are an increasingly important end-use in commercial office buildings. They currently account for 12-50% of total commercial building energy consumption, and as the efficiencies ofregulated major end-uses, such as space conditioning and lighting systems, continue to increase, plugload energy use is expected to rise. This study evaluates patterns in collected plug load data and the effect of a behavior-based intervention to reduce plug load energy consumption.This project leverages a data collection effort originally funded for a study by the California AirResources Board, where 100 plug load monitoring power strips were installed at individualworkstations in the Franklin Building, an office building in Oakland owned by the UC Office of thePresident (UCOP). Each occupant received one power strip and connected up to four devices to beindividually monitored. For this project, only the labeled devices (desktop, laptop, monitor, task light)are included. An analysis of the collected data reveals a clear distinction between work days and non-work days(weekends and holidays). Overall, the monitored occupants have regular work schedules, turn off theirequipment at the end of the work day, and do not often stay late or come in on the weekends. Desktops consume the most power per person, followed by monitors and then task lights. Laptop power trendswere more difficult to discern because users often disconnect them to work in other locations (that werenot monitored). Desktops demonstrate the widest range of power consumption among the devicesmonitored. During unoccupied periods (overnight and on non-work days), desktops draw the mostpower, followed by laptops. All devices draw more power overnight on work days than over weekendsand holidays, indicating that users are more likely to turn equipment off before a longer break from theoffice. Much of the literature on reducing plug load energy consumption in commercial buildings is focusedon technology-based solutions, such as purchasing new equipment or installing sophisticated controlsto turn off equipment when not in use. The literature on changing occupant behavior to reduce energyuse is focused on residential occupants, however multiple studies show that even when occupants donot pay their own bills and have no financial incentive to save energy, other factors can encouragebehavior change. One such motivating method is by using gamification, or turning an everyday activity into a game to encourage behavior change by making it more fun and interesting.With the help of leadership at UCOP, an online sustainability game, Cool Choices, was initiated in theFall of 2014 and 30 employees signed up to play. Cool Choices encourages occupant behavior changesto save water, energy, and reduce waste; players earn points for each action they complete at work or athome and compete with each other on teams. Survey responses from game participants showed thatplayers were motivated to play because the game looked fun, and because the actions suggested wereeasy to perform. An analysis of the energy impact revealed that because occupants were alreadyengaging in relevant energy saving behaviors (e.g. turning equipment off at the end of the day), therewas limited opportunity for further behavior-based reductions. Using trends identified in the baseline analysis, a simplified plug load model was developed to predictpower consumption based on device type, day type (work day or non-work day), and time step, using aMonte Carlo simulation. The model used day type and time step as proxies for occupancy, so when occupancy was not well predicted by the work day/non-work day dichotomy, the model becameincreasingly unreliable. Even after adding an additional variable (month), the model was still not ableto predict power consumption to an acceptable degree of accuracy per industry standards. The model demonstrated a need for a new, more accurate proxy for occupancy, perhaps based on individualoccupants, rather than devices.

Visual connection to nature has been demonstrated to have a positive impact on attention restoration, stress reduction, and overall health and well-being. Inside buildings, windows are the primary means of providing a connection to the outdoors, and nature views even through a window may have similar effects on the occupants. Given that humans recognize environments through multi-sensory integration, a window view may also affect occupants’ thermal perception. We assessed the influence of having a window with a view on thermal and emotional responses as well as on cognitive performance. We conducted a randomized crossover laboratory experiment with 86 participants, in spaces with and without windows. The chamber kept the air and window surface temperature at 28 °C, a slightly warm condition. The outcome measures consisted of subjective evaluations (e.g., thermal perception, emotion), skin temperature measurements and cognitive performance tests. In the space with versus without windows, the thermal sensation was significantly cooler (0.3 thermal sensation vote; equivalent to 0.74 °C lower), and 12% more participants were thermally comfortable. Positive emotions (e.g., happy, satisfied) were higher and negative emotions (e.g., sad, drowsy) were lower for the participants in the window versus the windowless condition. Working memory and the ability to concentrate were higher for participants in the space with versus without windows, but there were no significant differences in short-term memory, planning, and creativity performance. Considering the multiple effects of window access, providing a window with a view in a workplace is important for the comfort, emotion, and working memory and concentration of occupants.

Ceiling fans are a traditional approach for increasing occupant comfort and are well-established in residential application in many parts of the world. However, they are infrequently included in commercial spaces even though they have the potential to bring benefits including increased occupant comfort and decreased energy use either through raised setpoints in cooling or destratification in heating. This study provides practical insights into the case of ceiling fans in commercial spaces. We conducted 13 interviews with architects, engineers, and facilities managers from California and around the country to compile common themes of experience. These professionals provided lessons learned from 20 operational projects that include ceiling fans serving a wide set of functions in commercial spaces. Understanding the challenges they faced and the lessons they learned from these projects will facilitate prioritization of research and communication efforts. We also took in situ airspeed measurements at five of the projects to provide insight into real-world conditions in commercial buildings with ceiling fans. For these, the ceiling fans' operation results in generally relatively low airspeeds, often under 0.2 m/s. We also found just 25% of the 20 projects discussed by interviewees had any type of automation in the ceiling fan controls. This study serves as a resource for designers and for the wider industry, to frame a path forward for the inclusion of ceiling fans in commercial buildings.

This paper proposes and evaluates an integrated workflow that simultaneously uses ventilation, thermal, and luminous autonomy for the assessment of passive design strategies, introducing a potential way to integrate these three metrics in the design process. We developed a new metric, ventilation autonomy, and assessed the advantages and limitations of applying the three autonomy metrics with building performance simulations in two climates. We developed a novel visualization to display the hourly and yearly environmental autonomy values. The results show that when we consider the three metrics together, designers may have contradicting design directions if trying to both mitigate the solar radiation and to utilize natural ventilation. The visualizations that categorize nine combinations of thermal and visual comfort along with ventilation autonomy are effective in showing the trade-offs among ventilation, thermal, and visual performance.

Recognizing the value of open-source research databases in advancing the art and science of HVAC, in 2014 the ASHRAE Global Thermal Comfort Database II project was launched under the leadership of University of California at Berkeley's Center for the Built Environment and The University of Sydney's Indoor Environmental Quality (IEQ) Laboratory. The exercise began with a systematic collection and harmonization of raw data from the last two decades of thermal comfort field studies around the world. The ASHRAE Global Thermal Comfort Database II (Comfort Database), now an online, open-source database, includes approximately 81,846 complete sets of objective indoor climatic observations with accompanying ?right-here-right-now? subjective evaluations by the building occupants who were exposed to them. The database is intended to support diverse inquiries about thermal comfort in field settings. A simple web-based interface to the database enables filtering on multiple criteria, including building typology, occupancy type, subjects' demographic variables, subjective thermal comfort states, indoor thermal environmental criteria, calculated comfort indices, environmental control criteria and outdoor meteorological information. Furthermore, a web-based interactive thermal comfort visualization tool has been developed that allows end-users to quickly and interactively explore the data. The study was supported by the American Society of Heating, Refrigerating and Air-Conditioning Engineers grant ( URP 1656 ), 2016-2017 ASHRAE Graduate Grant-In-Aid for Veronika Fldvry Liina, British Council and UK Government under the Global Innovation Initiative project scheme, Korea National Science Foundation and the Center for the Built Environment, University of California Berkeley . Additional support was provided by the Republic of Singapore's National Research Foundation through a grant to the Berkeley Education Alliance for Research in Singapore (BEARS) for the Singapore-Berkeley Building Efficiency and Sustainability in the Tropics (SinBerBEST) Program. Scopus

Previous studies have demonstrated a potential reduction in cooling load and improvement in comfort from the implementation of night ventilation. This paper describes the performance, in terms of indoor environmental conditions, of three buildings from both the U.S. and India that use night ventilation as their primary cooling method. The research methods used the following approach: (1) Assess the cooling strategy in relation to the adaptive comfort model; (2) Develop a hybrid model, using both first principle equations and the collected data, to predict the instantaneous air and mass temperatures within each building and use the model to assess performance of the cooling strategy; (3) Determine an optimized ventilation control strategy for each building to minimize energy and maintain comfortable temperatures. (4) Develop a statistical model using collected data to predict the window opening pattern for occupants of a building using natural night ventilation. The study yielded the following results: (1) The buildings in the mild climate are successfully keeping the indoor temperature low, but also tend to be overcooling; (2) The night ventilation strategy has very little impact on indoor conditions of the buildings in the mild climate; (3) The impact of night ventilation is less significant when there is low internal loads and heavy mass; (4) The building in the hot and humid climate is keeping the indoor temperature within the comfort bounds for 88% of the year; (5) The night ventilation strategy has advantageous impact on indoor conditons of the building in the hot and humid climate, but not enough to cool the space on its own; (6) Model predictive control has the potential to further improve the performance of night ventilation. (7) Window opening behavior for the building using natural night ventilation is most heavily dependent on indoor air temperature and mass temperature.

India has diverse climatic conditions and study of adaptation can play important role for defining thermal comfort conditions in naturally ventilated buildings. Therefore, a field study of thermal comfort was carried out in thirty well ventilated residential and office buildings in composite climate region of India. The objective of the study is to evaluate the thermal environmental conditions and quantify thermal adaptation for occupants of these buildings. The study ascertains thermal neutrality and thermal acceptability and compares adaptation with field studies referred by a pool of researchers and scientists. The methodology of the study was through questionnaire administered to building occupants to record sensations and preferences for thermal environment variables. Simultaneously, physical measurements of environment variables were recorded considering class-II protocol of field measurements. During the study, the responses collected were 1811. The comfort temperature of the group was 27.21 °C for all seasons. The effects of seasonal variations on neutral temperature were also determined; respondents felt neutral at 25.6 °C, 27.0 °C and 29.4 °C during winter, moderate and summer seasons, respectively. Acceptable humidity and air velocity were 36% and 0.44 m/s for all seasons. Thermal acceptability for 90% and 80% were higher than the limits defined by comfort standards. Thermal acceptability reflected that study subjects were more adaptive to the thermal environment. The study observed that heat balance model of thermal comfort overestimated and underestimated thermal sensation during warm and cool thermal conditions, respectively. Furthermore, the study determines relationship between room temperature and comfort temperature with outdoor temperature.

A personal comfort model is a new approach to thermal comfort modeling that predicts individuals’ thermal comfort responses, instead of the average response of a large population. However, securing consistent occupant feedback for model development is challenging as the current methods of data collection rely on individuals’ survey participation. We explored the use of a new type of feedback, occupants’ heating and cooling behavior with a personal comfort system (PCS) for the development of personal comfort models to predict individuals’ thermal preference. The model development draws from field data including PCS control behavior, environmental conditions and mechanical system settings collected from 38 occupants in an office building, and employs six machine learning algorithms. The results showed that (1) personal comfort models based on all field data produced the median accuracy of 0.73 among all subjects and improved predictive accuracy compared to conventional models (PMV, adaptive) which produced a median accuracy of of 0.51; (2) the PMV and adaptive models produced individual comfort predictions only slightly better than random guessing under the relatively mild indoor environment observed in the field study; and (3) the models based on PCS control behavior produced the best prediction accuracy when individually assessing all categories of field data acquired in the study. We conclude that personal comfort models based on occupants’ heating and cooling behavior can effectively predict individuals’ thermal preference and can therefore be used in everyday comfort management to improve occupant satisfaction and energy use in buildings.

A personal comfort model is a new approach to thermal comfort modeling that predicts an individual's thermal comfort response, instead of the average response of a large population. It leverages the Internet of Things and machine learning to learn individuals' comfort requirements directly from the data collected in their everyday environment. Its results could be aggregated to predict comfort of a population. To provide guidance on future efforts in this emerging research area, this paper presents a unified framework for personal comfort models. We first define the problem by providing a brief discussion of existing thermal comfort models and their limitations for real-world applications, and then review the current state of research on personal comfort models including a summary of key advances and gaps. We then describe a modeling framework to establish fundamental concepts and methodologies for developing and evaluating personal comfort models, followed by a discussion of how such models can be integrated into indoor environmental controls. Lastly, we discuss the challenges and opportunities for applications of personal comfort models for building design, control, standards, and future research.

The building industry needs a fundamental paradigm shift in its notion of comfort, to find low-energy ways of creating more thermally dynamic and non-uniform environments that bring inhabitants pleasure. Strategies for providing enriched thermal environments must be conjoined with reducing energy; these are inseparable for any building striving for high performance. The objective of current comfort standards is to have no more than 20% of occupants dissatisfied, yet buildings are not reaching even that scant goal. A significant energy cost is incurred by the current practice of controlling buildings within a narrow range of temperatures (often over-cooling in the summer). If building designers and operators can find efficient ways to allow building temperatures to float over a wider range, while affording occupants individual control of comfort, the potential for energy savings is enormous. Five new ways of thinking, or paradigm shifts, are presented for designing or operating buildings to provide enhanced thermal experiences. They are supported by examples of research conducted by the Center for the Built Environment, and include shifts from centralized to personal control, from still to breezy air movement, from thermal neutrality to delight, from active to passive design, and from system disengagement to improved feedback loops.

The recent release of the largest database of thermal comfort field studies (ASHRAE Global Thermal Comfort Database II) presents an opportunity to perform a quality assurance exercise on the first generation adaptive comfort standards (ASHRAE 55 and EN15251). The analytical procedure used to develop the ASHRAE 55 adaptive standard was replicated on 60,321 comfort questionnaire records with accompanying measurement data. Results validated the standard's current adaptive comfort model for naturally ventilated buildings, while suggesting several potential nudges relating to the adaptive comfort standards, adaptive comfort theory, and building operational strategies. Adaptive comfort effects were observed in all regions represented in the new global database, but the neutral (comfort) temperatures in the Asian subset trended 1–2 °C higher than in Western countries. Moreover, sufficient data allowed the development of an adaptive model for mixed-mode buildings that closely aligned to the naturally ventilated counterpart. We present evidence that adaptive comfort processes are relevant to the occupants of all buildings, including those that are air conditioned, as the thermal environmental exposures driving adaptation occur indoors where we spend most of our time. This suggests significant opportunity to transition air conditioning practice into the adaptive framework by programming synoptic- and seasonal-scale set-point nudging into building automation systems.

Occupant window-opening behaviour in Indian offices is a nascent field. This paper relies on the thermal comfort field study data from 28 Indian offices in Hyderabad and Chennai. Occupants in naturally ventilated buildings used the windows and doors adaptively as the seasons changed and the temperature varied. We found that 50% of the windows would be opened at an indoor air temperature of 30 °C, using logistic regression. We noted some non-thermal factors possibly affecting the adaptive operation of controls as well, including: design and construction, operation and maintenance, environmental, sociocultural, attitudinal and behavioural factors. A window's potential for modifying the comfort temperature hinges on the effective handling of these hurdles. We further categorized the barriers into those in the occupant's realm and beyond. Each category is further identified with the extent to which the barrier interferes with the control as an adaptive opportunity.

The current Indian indoor comfort standards do not reflect the country's great cultural and climatic diversity. There have been very few reports on the actual environments in Indian offices in the last three decades. We conducted a thermal comfort field study in 28 naturally ventilated (NV) and air-conditioned (AC) offices in Chennai and Hyderabad for fourteen months, and collected 6048 responses from 2787 individuals. Warm humid and composite climates are experienced in these cities, and these two climates cover about 80% area of the country. This paper proposes an adaptive thermal comfort model for South India based on this data. Mean comfort temperature was found to be 28.0 °C in NV mode, and 26.4 °C in AC mode on all data. Chennai had slightly higher comfort temperature. We found an adaptive relationship between the prevailing outdoor temperature and the comfortable indoor temperatures. Most of the environments in NV mode and about half in AC mode were warmer than the current Indian Standard upper limit (26 °C). In most cases, the air speed was below 0.20 m/s. Most of the subjects used fans. Air speeds of 1 m/s increased the comfort temperature by 2.7 K in both the modes. Logistic regression predicted 87% and 50% fan usage at 29 °C in NV and AC modes respectively. Several factors prevented further thermal adaptation. We can potentially improve comfort and reduce air-conditioning by providing higher air speeds with energy-efficient fans. Such strategies may be vital given the scale of the scarcity of power.

Climate change and the urgency of decarbonizing the built environment are driving technological innovation in the way we deliver thermal comfort to occupants. These changes, in turn, seem to be setting the directions for contemporary thermal comfort research. This article presents a literature review of major changes, developments, and trends in the field of thermal comfort research over the last 20 years. One of the main paradigm shift was the fundamental conceptual reorientation that has taken place in thermal comfort thinking over the last 20 years; a shift away from the physically based determinism of Fanger’s comfort model toward the mainstream and acceptance of the adaptive comfort model. Another noticeable shift has been from the undesirable toward the desirable qualities of air movement. Additionally, sophisticated models covering the physics and physiology of the human body were developed, driven by the continuous challenge to model thermal comfort at the same anatomical resolution and to combine these localized signals into a coherent, global thermal perception. Finally, the demand for ever increasing building energy efficiency is pushing technological innovation in the way we deliver comfortable indoor environments. These trends, in turn, continue setting the directions for contemporary thermal comfort research for the next decades.

Mixed-mode buildings operate along a spectrum from sealed heating, ventilation and air-conditioning to 100% naturally ventilated, but little is known about their occupants' comfort expectations and experiences. Exceedance metrics, which quantify the percentage of time that a building's environment falls outside an expected thermal comfort zone, can help address the comfort trade-offs in building design and operation. Practitioners were polled on exceedance use in practice and comfort models and exceedance metrics were analysed: several comfort standards using EnergyPlus simulations of a mixed-mode building with radiant cooling in California's 16 climate zones. Results indicate that comfort model choice significantly influences predicted exceedance. Exceedance using PMV-PPD and the adaptive comfort models from ASHRAE Standard 55, EN 15251, and the Dutch NPR-CR 1752 frequently differed by 10 percentage points, often with 2–4 percentage points across the adaptive models. Yet, recommended exceedance limits of...

“Mixed-mode” refers to a hybrid approach to space conditioning that uses a combination of natural ventilation from operable windows (either manually or automatically controlled), and mechanical systems that provide air distribution and some form of cooling (air-conditioning, radiant cooling, etc.). By utilizing mechanical cooling only when and where it is necessary to supplement the natural ventilation, a well-designed mixed-mode building offers the potential to improve the indoor environmental quality while minimizing the significant energy and operating costs of air-conditioning. But there is limited information about the performance of mixed-mode buildings, particularly with regard to occupant satisfaction, and this can potentially be a powerful part of the argument to avoid or minimize the use of air-conditioning. This paper describes the results of web-based surveys conducted in 12 mixed-mode buildings, in comparison to our overall benchmarking survey database of 370 buildings, with over 43,000 individual responses. The survey focuses on seven areas of indoor environmental performance, including thermal comfort, air quality, acoustics, lighting, cleanliness, spatial layout, and office furnishings. The data shows that only 11% of the 370 buildings, most of which have conventional air-conditioning systems, are meeting the intent of the thermal comfort standards to achieve 80% satisfaction in the buildings. In comparison, the mixed-mode buildings are performing exceptionally well compared to the overall building stock, especially with regard to thermal comfort and air quality. Among the mixed-mode buildings, the best performers were those that were in more moderate climates, were newer, had radiant cooling or mechanical ventilation only (instead of an air-cooled system), and allowed high degrees of direct user control without changeover window interlock systems.

Buildings play a critical role in the challenge of mitigating and adapting to climate change. It is estimated that buildings contribute 39% of the total U.S. greenhouse gas (GHG) emissions [1] primarily due to their operational energy use, and about 80% of this building energy use is for heating, cooling, ventilating, and lighting. An important premise of this paper is about the connection between energy and comfort. They are inseparable when one talks about high performance buildings. Worldwide data suggests that we are significantly overcooling buildings in the summer, resulting in increased energy use and problems with thermal comfort. In contrast, in naturally ventilated buildings without mechanical cooling, people are comfortable in much warmer temperatures due to shifting expectations and preferences as a result of occupants having a greater degree of personal control over their thermal environment; they have also become more accustomed to variable conditions that closely reflect the natural rhythms of outdoor climate patterns. This has resulted in an adaptive comfort zone that offers significant potential for encouraging naturally ventilated buildings to improve both energy use and comfort. Research on other forms for providing individualized control through low-energy personal comfort systems (desktop fans, foot warmed, and heated and cooled chairs) have also demonstrated enormous potential for improving both energy and comfort performance. Studies have demonstrated high levels of comfort with these systems while ambient temperatures ranged from 64–84°F. Energy and indoor environmental quality are inextricably linked, and must both be important goals of a high performance building.

Current thermal comfort standards and the models underpinning them purport to be equally applicable across all types of building, ventilation, occupancy pattern and climate zone. A recent research project sponsored by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE, RP-884) critically evaluated these assumptions by statistically analysing a large database of research results in building comfort studies from all over the world (n=22,346). The results reported in this paper indicated a clear dependence of indoor comfort temperatures on outdoor air temperatures (instead of outdoor effective temperature ET* used in RP-884), especially in buildings that were free-running or naturally ventilated. These findings encourage significant revisions of ASHRAE’s comfort standard in terms of climatically relevant prescriptions. The paper highlights the potential for reduced cooling energy requirements by designing for natural or hybrid ventilation in many moderate climate zones of the world.

This paper presents the results of an extensive literature review on the topic of thermal adaptations in the built environment. The adaptive approach to modeling thermal comfort acknowledges the thermal perception in 'real world' settings is influenced by the complexities of past thermal history and cultural and technical practices. An important premise of the adaptive model is that the person is no longer a passive recipient of the given thermal environment, but instead is an active agent interacting with the person-environment systems via multiple feedback loops. The thermal adaptation can be attributed to three different processes--behavioral adjustment, physiological acclimatization and psychological habituation or expectation. Both climate chamber and field evidence indicates that the slower process of acclimatization is not so relevant to thermal adaptation in the relatively moderate conditions found in buildings, whereas behavioral adjustments and expectations have a much greater influence. One of the most important findings from our review of field evidence was the distinction between thermal comfort responses in air-conditioned vs. naturally ventilated buildings, most likely resulting from a combination of past thermal history in the buildings and differences in levels of perceived control.

Signalling systems that tell building occupants when to open and close windows have become a popular strategy for balancing the comfort benefits of manual windows with the efficiency benefits of automation in mixed-mode buildings. Data from surveys, interviews and site observations in 16 US buildings reveal a diversity of design objectives, control sequences and circumstances to anticipate when designing buildings with window signalling systems. The signals had the strongest influence on occupants’ use of windows when they were visible, the logic behind the controls algorithms was clearly understood, and they were seen as an informational device linked to an explicit internal policy that has to do with efficient and comfortable building operation. Lower levels of participation occurred when occupants tend not to pay attention to their windows, or the signals, unless they are uncomfortable, at which point it matters little what the signals indicate. However, occupants who do discover value in the signals are more likely to be more satisfied with their personal control. Occupants’ reasons for opening windows may include the desire for fresh air or air movement, which is as important to them as temperature adjustment, but admittedly difficult to program into the controls’ algorithms.

This paper discusses reassessment of indoor climate control in the context of current thermal comfort practice and research. We review the limitations of comfort models and standards with several examples. We examine how people's thermal sensation and preferences may be influenced by culture and climate and associated issues of thermal expectations and adaptation. Finally, we discuss how incorporating these factors into future comfort standards might yield more 'effective' indoor climate control.

Recently accepted revisions to ASHRAE Standard 55—thermal environmental conditions for human occupancy, include a new adaptive comfort standard (ACS) that allows warmer indoor temperatures for naturally ventilated buildings during summer and in warmer climate zones. The ACS is based on the analysis of 21,000 sets of raw data compiled from field studies in 160 buildings located on four continents in varied climatic zones. This paper summarizes this earlier adaptive comfort research, presents some of its findings for naturally ventilated buildings, and discusses the process of getting the ACS incorporated into Standard 55. We suggest ways the ACS could be used for the design, operation, or evaluation of buildings, and for research applications. We also use GIS mapping techniques to examine the energy-savings potential of the ACS on a regional scale across the US. Finally, we discuss related new directions for researchers and practitioners involved in the design of buildings and their environmental control systems.

This paper describes the logic of a microprocessor-controlled thermostat termed ‘comfortstat’ to address the needs of temporary room occupants such as hotel guests while reducing energy consumption. The ‘comfortstat’ design grew out of a study of thermal comfort control in a luxury hotel in San Francisco, California, USA. Hotel guests frequently arrive from widely disparate climates and have high expectations of the thermal environment. Their short-term occupancy (for periods ranging from one day to several weeks) provides a unique challenge for thermal comfort control. We examined the hotel complaint log, collected detailed physical measurements of the thermal environment in typical hotel rooms, assessed the HVAC (heating, ventilating and air-conditioning) system capacity and response time, and surveyed 315 hotel guests over a five-month period. The results of this study led to the design of a thermostat control system (the ‘comfortstat’) that would solve the most serious problems. The ‘comfortstat’ integrates an infrared occupancy sensor, door switch, radiant temperature sensor, and control logic to optimize room conditions while ‘learning’ about the occupant's preferred comfort zone. This paper focuses on how the joint requirements of the guests and the hotel management guided the design of the ‘comfortstat’ for increased occupant satisfaction and lower energy use in the hotel. The concepts are completely generic and could be applied to the design of comfort systems for other types of short-term occupancy. We present control logic flowcharts and typical examples of the action of the hotel ‘comfortstat’ in response to data received from the physical environment and/or human input.